docs: def collapse(batch_x, time_major=False):
      """ Converts timit into an array of format (batch_size, freq x num_deltas,
      time). Essentially, multiple channels are collapsed to one. """
  
      new_batch_x = []
      for utterance in batch_x:
          swapped = np.swapaxes(utterance, 0, 1)
          concatenated = np.concatenate(swapped, axis=1)
          new_batch_x.append(concatenated)
      new_batch_x = np.array(new_batch_x)
      if time_major:
          new_batch_x = np.transpose(new_batch_x, (1, 0, 2))
      return new_batch_x